In January 2015, an outbreak of undiagnosed human immunodeficiency virus (HIV) infections among persons who inject drugs (PWID) was recognized in rural Indiana. By September 2016, 205 persons in this community of approximately 4400 had received a diagnosis of HIV infection. Reports include the results of new approaches to analyzing epidemiologic and laboratory data to understand transmission during this outbreak.

Additionally, Dr. Duwve and colleagues calculated HIV genetic distances using the polymerase region generated networks using data about reported high-risk contacts, viral genetic similarity, and their most parsimonious combinations. They used sample collection dates and recency assay results to infer dates of infection. Epidemiologic and laboratory data each generated large and dense networks.

Integration of these data revealed subgroups with epidemiologic and genetic commonalities, one of which appeared to contain the earliest infections. Predicted infection dates suggest that transmission began in 2011, underwent explosive growth in mid-2014, and slowed after the declaration of a public health emergency.

It was also determined that persons infected with HIV in one genetic subgroup were among the earliest individuals infected during the outbreak. These same individuals were characterized as more likely to engage in high-risk sexual behavior than to use injection drugs.

When coupled with the lack of self-reported injection drug use behavior by the person with the earliest diagnosis of HIV infection, these findings suggest that high-risk sexual contact was the most plausible route by which HIV was introduced into this population of PWID.

The majority of HIV infections in the outbreak likely occurred prior to the declaration of a state public health emergency that included a syringe service program (SSP) for affected counties. Had an SSP been in place prior to recognition of the outbreak, the explosive phase of the outbreak may have been blunted.

These findings and methods may benefit future outbreak investigations by identifying, in near real-time and interactive fashion, subgroups or individuals at greatest risk for onward transmission of the pathogen and potential bridge individuals who could be prioritized for intervention as the outbreak evolves.

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